Article

Sun, W; Chretien, S; Biguri, A; Soleimani, M; Blumensath, T; Talbot, J (2023) The realisation of fast X-ray computed tomography using a limited number of projection images for dimensional metrology. NDT & E International, 137. 102852

Chretien, S; Giampiccolo, C; Sun, W; Talbott, J (2021) Fast hyperparameter calibration of sparsity enforcing penalties in Total Generalised Variation penalised reconstruction methods for XCT using a planted virtual reference image. Mathematics, 9 (22). 2960

Chretien, S; Cucuringu, M; Lecue, G; Neirac, L (2021) Learning with semi-definite programming: statistical bounds based on fixed point analysis and excess risk curvature. Journal of Machine Learning Research, 22 (230). pp. 1-64.

Lohvithee, M; Sun, W; Chretien, S; Soleimani, M (2021) Ant Colony-Based Hyperparameter Optimisation in Total Variation Reconstruction in X-ray Computed Tomography. Sensors, 21 (2). 591 ISSN 1424-8220

Chretien, S; Jagan, K; Barton, E (2020) Clustering on Laplacian-embedded latent manifolds when clusters overlap. Measurement Science and Technology, 31 (11). 114001 ISSN 0957-0233

Andreoli, L; Porte, X; Chretien, S; Jacquot, M; Larger, L; Brunner, D (2020) Boolean learning under noise-perturbations in hardware neural networks. Nanophotonics, 9 (13). pp. 4139-4147. ISSN 2192-8606

Chretien, S; Bondon, P (2020) Projection Methods for Uniformly Convex Expandable Sets. Mathematics, 8 (7). 1108 ISSN 2227-7390

Chretien, S; Lohvithee, M; Sun, W; Soleimani, M (2020) Efficient Hyper-Parameter Selection in Total Variation-Penalised XCT Reconstruction Using Freund and Shapire’s Hedge Approach. Mathematics, 8 (4). 493 ISSN 2227-7390

Assoweh, M I; Chretien, S; Tamadazte, B (2020) Spectrally Sparse Tensor Reconstruction in Optical Coherence Tomography Using Nuclear Norm Penalisation. Mathematics, 8 (4). 628 ISSN 2227-7390

Frangou, G J; Chretien, S; Rungger, I (2020) The First Quantum Co-processor Hybrid for Processing Quantum Point Cloud Multimodal Sensor Data. Advances in Intelligent Systems and Computing, 1069. pp. 411-426. ISSN 2194-5357

Chretien, S; Tyagi, H (2020) Multi-kernel Unmixing and Super-Resolution Using the Modified Matrix Pencil Method. Journal of Fourier Analysis and Applications, 26 (1). 18 ISSN 1069-5869

Matar, J; El Khoury, H; Charr, J C; Guyeux, C; Chretien, S (2019) SpCLUST: Towards a fast and reliable clustering for potentially divergent biological sequences. Computers in Biology and Medicine, 114. 103439 ISSN 00104825

Chretien, S (2019) Corrigendum to “A note on computing the Smallest Conic Singular Value” [J. Comput. Appl. Math. 340 (2018) 221–230]. Journal of Computational and Applied Mathematics, 347. p. 369. ISSN 03770427

Chretien, S (2018) A note on computing the smallest conic singular value. Journal of Computational and Applied Mathematics, 340. pp. 221-230. ISSN 03770427

Chretien, S; Clarkson, P (2018) Application of robust PCA with a structured outlier matrix to topology estimation in power grids. International Journal of Electrical Power & Energy Systems, 100. pp. 559-564.

Chretien, S; Wei, T W (2018) On the subdifferential of symmetric convex functions of the spectrum for symmetric and orthogonally decomposable tensors. Linear Algebra and its Applications, 542. pp. 84-100.

Bruneau, M; Mottet, T; Moulin, S; Kerbiriou, M; Chouly, F; Chretien, S; Guyeux, C (2018) A clustering package for nucleotide sequences using Laplacian Eigenmaps and Gaussian Mixture Model. Computers in Biology and Medicine, 93. pp. 66-74. ISSN 00104825

Al Sarray, B; Chretien, S; Clarkson, P; Cottez, G (2017) Enhancing Prony's method by nuclear norm penalization and extension to missing data. Signal Image and Video Processing, 11 (6). pp. 1089-1096.

Moulin, S*; Seux, N*; Chretien, S; Guyeux, C*; Lerat, E* (2017) Simulation-based estimation of branching models for LTR retrotransposons. Bioinformatics, 33 (3). pp. 320-326.

Chretien, S; Guyeux, C*; Conesa, B*; Delage-Mouroux, R*; Jouvenot, M*; Huetz, P*; Descotes, F* (2016) A Bregman-proximal point algorithm for robust non-negative matrix factorization with possible missing values and outlines- application to gene expression analysis. BMC Bioinformatics, 17 (8). p. 284.

Chretien, S; Herr, N; Nicod, J-M; Varnier, C* (2016) Post-prognostics decision for optimizing the commitment of fuel cell systems. IFAC - Papers Online, 49 (28). pp. 168-173.

Chretien, S; Corset, F* (2016) A lower bound on the expected optimal value of certain random linear programs and application to shortest paths in directed acyclic graphs and reliability. Statistics & Probability Letters, 117. pp. 221-230.

Conference or Workshop Item

Chretien, S; Thompson, A; Toader, B (2019) The dual approach to non-negative super-resolution: impact on primal reconstruction accuracy. In: 2019 13th International Conference on Sampling Theory and Applications (SampTA), 8-12 July 2019, Bordeaux, France.

Wei, T; Chretien, S (2019) A Penalized Autoencoder Approach for Nonlinear Independent Component Analysis. In: 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 12-17 May 2019, Brighton, UK.

Chretien, S; Ho, O (2018) Feature Selection in Weakly Coherent Matrices. In: Latent Variable Analysis and Signal Separation. 14th International Conference, LVA/ICA, 2-5 July 2018, Guildford, UK.

Segovia, M; Rohouma, I; Hong, Q T; Chretien, S; Clarkson, P (2017) Validation of algorithms to estimation network characteristics using power-hardware-in-the-loop configuration. In: 2017 IEEE Workshop on Applied Measurements for Power Systems (AMPS), 22-22 September 2017, Liverpool, UK.

Chretien, S; Harris, P M; Tawil, R* (2016) Total Variation minimization for Compressed Sensing with "smoothly'' varying covariates. In: 19th IEEE International Conference on Computational Science and Engineering (CSE), IEEE 14th International Conference on Embedded and Ubiquitous Computing (EUC) and 15th International Symposium on Distributed Computing and Applications for Business Engine, 24-26 August 2016, Paris, France.

Book Chapter/Section

Chretien, S; Dares, S (2018) An elementary approach to the problem of column selection in a rectangular matrix. In: Lecture Notes in Computer Science - Machine Learning, Optimization and Big Data. Springer, pp. 234-243. ISBN 9783319729251